It took nearly a century to figure out just 430 of these Nazca geoglyphs, but now AI nearly doubled the number overnight, adding 303 new geoglyphs to our knowledge.
AI might've also revealed why the Nazca lines were constructed!🧵
For background, the Nazca lines are a set of exceptionally well-preserved geoglyphs and walking routes that exist in the agriculturally-unsuitable Nazca Pampa region.
The traditionally-known lines seem to depict things that make sense. For example, here's a spider:
Line construction is a practice from the region that's at least 2,000 years old and it results in lots of very interpretable pictures, like this monkey:
The lines have been classified into many types.
It's believed that the different types are distributed in geographically distinct areas, created in different times, and most obviously, that they have different meanings.
The new lines discovered by AI are a bit harder for humans to understand or pick out, but when the AI points them out, it becomes apparent we were overlooking them, perhaps because they're so weird and foreign to us
They're also older and smaller than known ones. Take a look:
These newly-discovered Nazca lines depict very figurative rather than literal shapes, but they also depict ritual, and maybe even lawgiving or war.
These lines are weird precisely because they had to be distinct to suit their purpose.
I'll come back to this.
The new lines were found by the AI like so.
The AI highlighted certain areas as being particularly 'line-like' (A), and then the researchers visually inspected the photographs the AI had been provided (B).
After the AI pointed it out, it was often clear something was there.
This exercise was repeated over and over again throughout the whole region between Lima and Nazca, leading to a lot of new targets.
The team then set out on foot and by drone to see if the lines were real, in-person.
Real lines are clearly dug into the ground and often contain artefacts like pottery shards and such.
The AI found them and the humans confirmed them.
A very large number of these new discoveries went overlooked for so long because they were reliefs.
Reliefs are less distinct in the landscape, but are still persistent, like the better-known lines. They also depict different things than the lines do:
When you look at the reliefs, you'll see evidence of ancient domestication and lawgiving or warring.
The lines, however, more often just depict an animal. Why might they be so different? It's not like the complexity differed all that much.
Here's the meat:
What makes these lines so interesting is that the AI makes it clear that they had distinct purposes.
The relief-type lines that show people and such? Well, those mark trail-heads. They're less distinct because you're intended to be close to them!
If you wanted to navigate across the region, you could walk until you saw a certain relief, and then you'd know what trail to take!
Critically, this network was informal. The state, however, made a formal network leading to the Cahuachi Pyramids, which were a ceremonial center.
The lines rather than reliefs are younger because they're associated with state formation/organization.
The region's state co-opted the informal, cultural practice of making reliefs for navigation in order to set up the line network to get to and be seen from the temple complex!
And there we have it! We might now know the purpose of and who funded the Nazca lines. (Thanks, AI!)
To review, there's an old, informal line network used for navigation. You walk up a trail, you see a relief. The number of these known just blew up due to AI.
The old informal line network where you see a relief then you go down the right trail was formalized by the region's state to create massive lines, sharp breaks that are more obvious from a distance
These lead to and support the temple complex, facilitating worship/organization
And guess what? With the power of AI, we're just getting started.
The authors of the study said that there are more than 250 additional geoglyphs flagged by the AI, which they didn't have the time to examine in person.
What else will we learn about this ancient civilization?
This research directly militates against modern blood libel.
If people knew, for example, that Black and White men earned the same amounts on average at the same IQs, they would likely be a lot less convinced by basically-false discrimination narratives blaming Whites.
Add in that the intelligence differences cannot be explained by discrimination—because there *is* measurement invariance—and these sorts of findings are incredibly damning for discrimination-based narratives of racial inequality.
So, said findings must be condemned, proscribed.
The above chart is from the NLSY '79, but it replicates in plenty of other datasets, because it is broadly true.
For example, here are three independent replications:
A lot of the major pieces of civil rights legislation were passed by White elites who were upset at the violence generated by the Great Migration and the riots.
Because of his association with this violence, most people at the time came to dislike MLK.
It's only *after* his death, and with his public beatification that he's come to enjoy a good reputation.
This comic from 1967 is a much better summation of how the public viewed him than what people are generally taught today.
And yes, he was viewed better by Blacks than by Whites.
But remember, at the time, Whites were almost nine-tenths of the population.
Near his death, Whites were maybe one-quarter favorable to MLK, and most of that favorability was weak.
The researcher who put together these numbers was investigated and almost charged with a crime for bringing these numbers to light when she hadn't received permission.
Greater Male Variability rarely makes for an adequate explanation of sex differences in performance.
One exception may be the number of papers published by academics.
If you remove the top 7.5% of men, there's no longer a gap!
The disciplines covered here were ones with relatively equal sex ratios: Education, Nursing & Caring Science, Psychology, Public Health, Sociology, and Social Work.
Because these are stats on professors, this means that if there's greater male variability, it's mostly right-tail
Despite this, the very highest-performing women actually outperformed the very highest-performing men on average, albeit slightly.
The percentiles in this image are for the combined group, so these findings coexist for composition reasons.